Gemini 3.6 Flash vs Gemini 3.8 Flash
Full profiles: Gemini 3.6 Flash (Google) and Gemini 3.8 Flash (Google): every benchmark, price and rank.
Updated · Data from 12 sources
As of 2 Nov 2026, Gemini 3.6 Flash and Gemini 3.8 Flash are neck and neck on quality (61.3 vs 61.9 on the BenchLeader Index, inside the ±4.8 margin), and they cost about the same at $1.50 vs $1.50 per 1M tokens blended. Choose 3.6 Flash for agents & tools (59 vs 51) and fast first answers (16.4 s vs 24.9 s), where it also streams ~1.5× faster; choose 3.8 Flash for coding (60 vs 57), maths (62 vs 59), and multimodal (68 vs 65). Both prices are promotional: Gemini 3.6 Flash goes to $3.00 on 1 Jan 2027 and Gemini 3.8 Flash to $3.00 on 1 Jan 2027.
Key facts (as of 2 Nov 2026)
- Gemini 3.6 Flash scores 61.3 on the BenchLeader Index and Gemini 3.8 Flash scores 61.9 (BenchLeader, 2 Nov 2026).
- Gemini 3.6 Flash costs $1.50 per 1M tokens blended until 31 Dec 2026, then $3.00 (https://ai.google.dev/gemini-api/docs/pricing, checked 20 Oct 2026).
- Gemini 3.8 Flash costs $1.50 per 1M tokens blended until 31 Dec 2026, then $3.00 (https://ai.google.dev/gemini-api/docs/pricing, checked 20 Oct 2026).
- Gemini 3.6 Flash streams ~1.5× faster than Gemini 3.8 Flash (Artificial Analysis, 7-day median, 2 Nov 2026).
- Of the 68 benchmarks both models have, Gemini 3.8 Flash leads 61 (BenchLeader, 2 Nov 2026).
- On Arena WebDev, Gemini 3.6 Flash is rated 1538 and Gemini 3.8 Flash 1583 (LMArena, as published by 2 Nov 2026).
Gemini 3.6 Flash benchmarks Which to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Gemini 3.8 Flash | 60 vs 57 category score; Arena WebDev 1583 vs 1538 | Medium |
| Agents & tool use | Gemini 3.6 Flash | 59 vs 51 category score; τ³-Banking (AA) 29.9% vs 45.0% | High |
| Maths | Gemini 3.8 Flash | 62 vs 59 category score; FrontierMath Tiers 1–3 68.4% vs 59.0% | Medium |
| Reasoning | Either | 64 vs 64 category score; GPQA Diamond 94.1% vs 95.4% | Either |
| Knowledge | Either | 64 vs 64 category score; SimpleQA Verified 66.2% vs 69.7% | Either |
| Long documents | Either | 65 vs 66 category score; AA-LCR v1.1 80.0% vs 81.3% | Either |
| Images and other media | Gemini 3.8 Flash | 68 vs 65 category score; Arena Vision 1315 vs 1299 | Medium |
| Chat quality (human preference) | Gemini 3.8 Flash | 69 vs 67 on Arena votes | Medium |
| Lowest cost | Either | $1.50 vs $1.50 per 1M blended; agentic coding session $0.060 vs $0.060; from 1 Jan 2027: $3.00 vs $3.00 | – |
| Fastest first answer | Gemini 3.6 Flash | 16.4 s (Gemini 3.6 Flash (high)) vs 24.9 s (Gemini 3.8 Flash (high)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- Gemini 3.6 Flash (high) and Gemini 3.8 Flash (high) are neck and neck on quality (61.3 vs 61.9, within the ±4.8 margin).
- Gemini 3.6 Flash (high) is stronger in agents & tools, reasoning.
- Gemini 3.8 Flash (high) is stronger in coding, human preference, knowledge, long context, maths, multimodal.
- They cost about the same ($1.50 per 1M blended) until 31 Dec 2026, then $3.00 vs $3.00 from 1 Jan 2027.
- Gemini 3.6 Flash (high) streams 1.5× faster (197 vs 131 tokens per second).
At a glance
| Spec | Gemini 3.6 Flash | Gemini 3.8 Flash |
|---|---|---|
| Developer | ||
| Released | 21 Jul 2026 | 2 Sep 2026 |
| Context window (tokens) | 1,048,576 | 1,048,576 |
| Compared at | Gemini 3.6 Flash (high) | Gemini 3.8 Flash (high) |
| Open weights | No | No |
| Price in / out / cached input per 1M | $0.750 / $3.75 / $0.075 | $0.750 / $3.75 / $0.075 |
| Announced price change | $1.50 / $7.50 / $0.150 from 1 Jan 2027 | $1.50 / $7.50 from 1 Jan 2027 |
Limits, availability and announced prices from the vendors' own pages: ai.google.dev pricing (checked 20 Oct 2026). Everything else is from the day's data.
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | Gemini 3.6 Flash (high) | Gemini 3.8 Flash (high) | Leader |
|---|---|---|---|
| Reasoning | 64.0 | 63.8 | level |
| Coding | 56.9 | 60.2 | Gemini 3.8 Flash |
| Agents & tools | 59.3 | 51.1 | Gemini 3.6 Flash |
| Maths | 59.4 | 62.2 | Gemini 3.8 Flash |
| Knowledge | 63.8 | 64.4 | level |
| Human preference | 67.4 | 69.0 | Gemini 3.8 Flash |
| Multimodal | 65.2 | 67.5 | Gemini 3.8 Flash |
| Long context | 64.8 | 65.5 | level |
On one chart
Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.
Not drawn, measured for fewer than two of these models: Instruction following.
ModelIndex
Where sources disagree
Across the 68 benchmarks both have, Gemini 3.6 Flash leads 6, Gemini 3.8 Flash leads 61 and 1 is a tie. Every overall index that rates both puts Gemini 3.8 Flash ahead.
| Overall index | Gemini 3.6 Flash (high) | Gemini 3.8 Flash (high) | Leader |
|---|---|---|---|
| BenchLeader Index | 61.3 | 61.9 | neck and neck |
| Arena Text | 1483 | 1496 | Gemini 3.8 Flash |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.
| Measure | Gemini 3.6 Flash (high) | Gemini 3.8 Flash (high) |
|---|---|---|
| Blended price per 1M tokens, until 31 Dec 2026 | $1.50 | $1.50 |
| Input / output per 1M | $0.750 / $3.75 | $0.750 / $3.75 |
| Blended price per 1M from 1 Jan 2027 | $3.00 | $3.00 |
| Input / output per 1M from 1 Jan 2027 | $1.50 / $7.50 | $1.50 / $7.50 |
| Cached input per 1M | $0.075 | $0.075 |
| Price per task: chat reply | $0.0014 | $0.0014 |
| Price per task: summarize a 30-page report | $0.011 | $0.011 |
| Price per task: code edit | $0.010 | $0.010 |
| Price per task: agentic coding session | $0.060 | $0.060 |
| Price per task: structured extraction | $0.0023 | $0.0023 |
| Agentic coding session, input mostly cached | $0.030 | $0.030 |
| Cost per benchmark task (AA Index) | – | $7.77 |
| Output tokens per task (AA Index) | – | 99k |
| Of which reasoning | – | 60k |
| Time per task (AA Index) | – | 12 min |
| Output speed | 197 tok/s | 131 tok/s |
| Time to first answer | 16.4 s | 24.9 s |
| Time to a complete answer | 18.9 s | 28.7 s |
Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.6 Flash (high) scores 61.3 and takes 16 s to its first answer token; Gemini 3.6 Flash scores 49.5 in 1 s. Gemini 3.8 Flash (high) scores 61.9 and takes 25 s to its first answer token; Gemini 3.8 Flash (medium) scores 60.6 in 3 s, Gemini 3.8 Flash (low) scores 56.1 in 3 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
152 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | Gemini 3.6 Flash (high) | Gemini 3.8 Flash (high) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 61.3 | 61.9 |
| Agents & tools score | BenchLeader | 59.3 | 51.1 |
| Coding score | BenchLeader | 56.9 | 60.2 |
| Human preference score | BenchLeader | 67.4 | 69.0 |
| Knowledge score | BenchLeader | 63.8 | 64.4 |
| Long context score | BenchLeader | 64.8 | 65.5 |
| Maths score | BenchLeader | 59.4 | 62.2 |
| Multimodal score | BenchLeader | 65.2 | 67.5 |
| Reasoning score | BenchLeader | 64.0 | 63.8 |
| Blended price $/M | BenchLeader | $1.50 | $1.50 |
| Output speed | BenchLeader | 197 tok/s | 131 tok/s |
| Time to first answer | BenchLeader | 16.4 s | 24.9 s |
| Context window | BenchLeader | 1,048,576 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 94.1% | 95.4% |
| Humanity's Last Exam | Scale AI / CAIS | – | 44.5%† |
| Arena Hard Prompts | Arena (LMArena) | 1501 | 1517 |
| LiveBench 2.0 Reasoning | LiveBench | – | 89.3%† |
| LiveBench 1.0 Reasoning | LiveBench | 85.2% | 89.3% |
| GPQA Diamond (AA) | Artificial Analysis | 92.8% | 95.3% |
| Humanity's Last Exam (AA) | Artificial Analysis | 40.8% | 47.8% |
| HLE-Diamond (AA) | Artificial Analysis | – | 33.1% |
| GPQA Diamond (Vals) | Vals AI | 93.4% | 94.4% |
| ARC-AGI-1 | ARC Prize | 91.2% | 98.5% |
| ARC-AGI-2 | ARC Prize | 60.4% | 89.2% |
| ARC-AGI-3 | ARC Prize | – | 35.0% |
| CritPt | Artificial Analysis | 10.6% | 18.3% |
| CritPt v2 hard subset (AA) | Artificial Analysis | – | 43.5% |
| MysteryMechanism | Vals AI | – | 36.5% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 40.0% | 58.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 30.0% | 47.0% |
| LMCA | Epoch AI Benchmarking Hub | 44.9% | 51.5%† |
| DTBench | Epoch AI Benchmarking Hub | 95.5% | 95.7%† |
| ForecastBench | ForecastBench | 65.9%† | – |
| Coding | |||
| SciCode | SciCode | 53.4% | 56.6% |
| WeirdML | WeirdML | 56.1% | 84.8% |
| FrontierCode | Cognition | 34.4%† | 41.2%† |
| Arena Coding | Arena (LMArena) | 1518 | 1530 |
| Arena WebDev | Arena (LMArena) | 1538 | 1583 |
Show all 152 benchmarks
| Metric | Publisher | Gemini 3.6 Flash (high) | Gemini 3.8 Flash (high) |
|---|---|---|---|
| Coding | |||
| LiveBench 2.0 Coding | LiveBench | – | 82.2%† |
| LiveBench 1.0 Coding | LiveBench | 77.9% | 72.5% |
| LiveCodeBench | Vals AI | 88.1% | 89.5% |
| IOI | Vals AI | 35.1% | 56.9% |
| SWE-bench (Vals) | Vals AI | 79.6% | 80.0% |
| Code Migration | Vals AI | 30.9% | 36.5% |
| Code Migration v1.1 | Vals AI | – | 38.6% |
| ProgramBench | Vals AI | 0.0% | 1.0% |
| SWE-bench Multimodal | Vals AI | – | 40.8% |
| Vibe Code Bench 1-100 | Vals AI | – | 18.8% |
| Vibe Code Bench v1.1 | Vals AI | 64.0% | 78.7% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | – | 47.0%† |
| SWE Atlas: Refactoring | Scale AI SEAL | – | 44.8%† |
| SWE Atlas: Test Writing | Scale AI SEAL | – | 53.7%† |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | – | 76.9% |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 46.7% | 73.8% |
| CursorBench | Cursor | – | 39.6% |
| ALE-Bench | Epoch AI Benchmarking Hub | 715.5 | 1269.7 |
| FrontierSWE | Epoch AI Benchmarking Hub | – | 19.6% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 7.1% | 19.7% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 77.5% | 87.6% |
| Startrise Frontend | Startrise | – | 64.6%† |
| GameBench 2 Overall | DuelLab GameBench 2 | 52.5† | 61.0† |
| GameBench 2 by reasoning setting | DuelLab GameBench 2 | 64.6 | 66.2 |
| FrontierCode 1.1 (AA) | Artificial Analysis | – | 36.4% |
| FrontierCode 2.0 (AA) | Artificial Analysis | – | 18.7% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | – | 19.1% |
| Remote Labor Index | Scale AI / CAIS | – | 5.8%† |
| APEX-Agents | Mercor | 46.9%† | 64.3%† |
| Arena Agent | Arena (LMArena) | – | 2.6 |
| LiveBench Long Agentic | LiveBench | – | 16.5%† |
| LiveBench Browser | LiveBench | – | 45.1%† |
| LiveBench Agentic Coding | LiveBench | 43.4% | 54.2% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 73.8% | 81.3% |
| HiL-Bench | Scale AI SEAL | – | 41.5%† |
| GDPval-AA v2.1, normalised score | Artificial Analysis | – | 46.8% |
| GDPval-AA v2.1 | Artificial Analysis | – | 1445 |
| τ³-Banking (AA) | Artificial Analysis | 29.9% | 45.0% |
| ITBench SRE (AA) | Artificial Analysis | – | 52.5% |
| Analyst Agent (AA) | Artificial Analysis | – | 46.3% |
| CUA-bench | Vals AI | – | 4.2% |
| CyberBench | Vals AI | 45.4% | 43.8% |
| Finance Agent v2 | Vals AI | 56.3% | 61.4% |
| Finance Agent v2.1 | Vals AI | – | 65.8% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | – | 12.1% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 3.3% | 10.0% |
| Legal Research Bench | Vals AI | 25.0% | 38.9% |
| SkillsBench | Vals AI | – | 58.0% |
| SREBench | Vals AI | – | 11.1% |
| Tax Agent Bench | Vals AI | 18.0% | 32.1% |
| Terminal-Bench 4.0 (Vals) | Vals AI | – | 19.7% |
| Terminal-Bench Science | Vals AI | 4.3% | 8.6% |
| Time Horizon Index: KSP | Vals AI | – | 18.8% |
| Vending-Bench 2 | Andon Labs | – | 5093.8† |
| AutomationBench | Artificial Analysis | 53.0% | 59.9% |
| GDP.pdf (AA) | Artificial Analysis | 17.4% | 21.0% |
| Harvey LAB-AA v1.1 | Harvey | – | 0.0% |
| AA-Briefcase v1.1 | Artificial Analysis | – | 1203 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | – | 10.0% |
| CWE-Bench (AA) | Artificial Analysis | – | 52.5% |
| DeepSec-Bench (AA) | Artificial Analysis | – | 14.5% |
| CyberGym end-to-end (AA) | Artificial Analysis | – | 8.4% |
| FACTS Search | 68.2%† | 76.3%† | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 59.0% | 68.4% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 21.9% | 21.9% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 94.2% | 98.9% |
| ProofBench | Vals AI | 36.0%† | 48.0%† |
| LiveBench Mathematics | LiveBench | 86.4% | 91.6% |
| AIME 2026 | MathArena | 96.7%† | – |
| HMMT February 2026 | MathArena | 89.4%† | – |
| MathArena Apex | MathArena | 26.0%† | – |
| Arena Maths | Arena (LMArena) | 1504 | 1524 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 66.2% | 69.7% |
| LiveBench 2.0 Data Analysis | LiveBench | – | 54.0%† |
| LiveBench Research | LiveBench | – | 79.1%† |
| LiveBench 1.0 Data Analysis | LiveBench | 63.0% | 54.0% |
| AA-Omniscience v1.1 | Artificial Analysis | – | 23.3 |
| MMLU-Pro | Vals AI | 89.3% | 90.2% |
| LegalBench | Vals AI | 86.7% | 87.0% |
| CorpFin | Vals AI | 63.3% | – |
| TaxEval | Vals AI | 74.9% | 74.5% |
| PRBench Finance | Scale AI SEAL | – | 49.5%† |
| PRBench Legal | Scale AI SEAL | – | 48.9%† |
| BioMysteryBench | Vals AI | 58.5% | 62.2% |
| Excel Modeling Benchmark | Vals AI | 65.4% | 72.2% |
| Excel Modeling Benchmark v1.1 | Vals AI | – | 72.9% |
| MedCode | Vals AI | 53.1% | 48.1% |
| MedScribe | Vals AI | 79.7% | 84.5% |
| Public Benefits Bench v1.1 | Vals AI | 56.6% | 65.3% |
| GDP.pdf | Epoch AI Benchmarking Hub | 14.0% | 23.2% |
| AA-Omniscience v1.1: accuracy | Artificial Analysis | – | 50.5% |
| AA-Omniscience v1.1: non-hallucination | Artificial Analysis | – | 44.9% |
| HealthBench Professional (AA) | OpenAI | – | 51.7% |
| Instruction following | |||
| LiveBench Language | LiveBench | 83.9% | 87.8% |
| LiveBench Instruction Following | LiveBench | 75.4% | 81.4% |
| Arena Instruction Following | Arena (LMArena) | 1473 | 1491 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1483 | 1496 |
| Arena Creative Writing | Arena (LMArena) | 1471 | 1487 |
| Arena Multi-turn | Arena (LMArena) | 1488 | 1505 |
| Arena Longer Queries | Arena (LMArena) | 1485 | 1512 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1299 | 1315 |
| LiveBench Design | LiveBench | – | 72.7%† |
| MMMU-Pro | Artificial Analysis | 83.2% | 85.6% |
| MMMU-Pro (Vals) | Vals AI | 88.4% | 89.1% |
| MortgageTax | Vals AI | 67.6% | 65.3% |
| SAGE | Vals AI | – | 88.2% |
| AudioMC | Scale AI SEAL | – | 60.4% |
| AudioMC (text output) | Scale AI SEAL | – | 60.4% |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 31.2%† | 38.6%† |
| Code2Video-AA | Artificial Analysis | – | 899 |
| AA-3D | Artificial Analysis | – | 966 |
| Long context | |||
| AA-LCR v1.1 | Artificial Analysis | 80.0% | 81.3% |
| Arena Document | Arena (LMArena) | 1453 | – |
| MLCR | Artificial Analysis | 10.0% | 10.6% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 154.7† | 157.6† |
| LiveBench 2.0 | LiveBench | – | 59.2%† |
| LiveBench 1.0 | LiveBench | 73.6% | 75.8% |
| AA Intelligence Index v5.0 | Artificial Analysis | – | 30.6 |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 34.0 | 40.9 |
| AA Progress Index v1 | Artificial Analysis | 305.7 | 320.3 |
| Vals Index | Vals AI | – | 56.0 |
| Vals Finance Index | Vals AI | – | 60.5% |
| Vals RSI Index | Vals AI | – | 19.9% |
| Vals Science Index | Vals AI | – | 35.8% |
| Vals Multimodal Index | Vals AI | 65.1% | – |
| Vals Router Index | Vals AI | – | 56.0%† |
| AA Cyber Index | Artificial Analysis | – | 25.1 |
Data as of 2026-11-02. Best configuration of each model; every score links to its source on the model pages.
DuelLab GameBench 2, release gb2-20261026-cb69502a12d9 (https://benchmarks.duellab.org/releases/gb2-20261026-cb69502a12d9/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.
What changed
- Gemini 3.6 Flash: list price moves to $1.50 / $7.50 per 1M input / output tokens (announced).
- Gemini 3.8 Flash: list price moves to $1.50 / $7.50 per 1M input / output tokens (announced).
- Gemini 3.8 Flash (high): 1 new result (MirrorCode).
- Gemini 3.8 Flash (high): 1 score revision.
- Gemini 3.6 Flash (high): BenchLeader Index 61.8 → 61.2.
- Gemini 3.8 Flash (high): BenchLeader Index 63.3 → 61.8.
- Gemini 3.6 Flash (high): 1 new result (AA Progress Index v1).
- Gemini 3.8 Flash (high): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 3 score revisions; cost per task moved from $3.49/M to $7.77/M (123% up).
- Gemini 3.8 Flash (high): cost per task moved from $1.24/M to $3.49/M (180% up).
- Gemini 3.6 Flash (high): 1 new result (Harvey's Legal Agent Benchmark v1).
Related comparisons
- Gemini 3.6 Flash vs Claude Opus 5.5
- Gemini 3.6 Flash vs Gemini 4 Carbon
- Gemini 3.6 Flash vs GPT-6 Astra
- Gemini 3.8 Flash vs Claude Opus 5.5
- Gemini 3.8 Flash vs Gemini 4 Carbon
- Gemini 3.8 Flash vs GPT-6 Astra
- Gemini 3.8 Flash vs GPT-6.1 Sol
- Gemini 3.5 Flash vs Gemini 3.8 Flash
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
Gemini 3.6 Flash vs Gemini 3.8 Flash: questions
- Is Gemini 3.6 Flash better than Gemini 3.8 Flash?
- Gemini 3.6 Flash (high) and Gemini 3.8 Flash (high) are neck and neck on quality (61.3 vs 61.9, within the ±4.8 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2 Nov 2026, so check the category scores for your use.
- Gemini 3.6 Flash vs Gemini 3.8 Flash: which is cheaper, and will that change?
- They cost the same: $1.50 per million tokens blended. Gemini 3.6 Flash's current price runs until 31 Dec 2026, then $3.00. Gemini 3.8 Flash's current price runs until 31 Dec 2026, then $3.00.
- Is Gemini 3.6 Flash or Gemini 3.8 Flash better for coding?
- Gemini 3.8 Flash scores higher in coding (60 vs 57 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1538 for Gemini 3.6 Flash against 1583 for Gemini 3.8 Flash.
- Which is faster, Gemini 3.6 Flash or Gemini 3.8 Flash?
- Gemini 3.6 Flash streams ~1.5× faster (197 vs 131 output tokens per second, Artificial Analysis 7-day median).
- Is Gemini 3.6 Flash or Gemini 3.8 Flash better for agents and tool use?
- Gemini 3.6 Flash scores higher in agentic tasks (59 vs 51 on the category index, where 50 is average). On τ³-Banking (AA), the top shared agents & tools benchmark, it is 29.9% for Gemini 3.6 Flash against 45.0% for Gemini 3.8 Flash.
More questions (4)
- Which is better for long documents?
- They are level on long-context benchmarks (65 vs 66). Both accept 1,048,576 tokens of context.
- Which has lower latency?
- Gemini 3.6 Flash answers first: 16.4 s against 24.9 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Do independent benchmarks agree on Gemini 3.6 Flash vs Gemini 3.8 Flash?
- Across the 68 benchmarks both have, Gemini 3.6 Flash leads 6, Gemini 3.8 Flash leads 61 and 1 is a tie. Every overall index that rates both puts Gemini 3.8 Flash ahead.
- When was Gemini 3.8 Flash released?
- Gemini 3.8 Flash was released on 2 Sep 2026.